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Exam 10: Quality Control

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Question 21

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Control limits tend to be wider for more variable processes.

A) True
B) False

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Question 22

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A time-ordered plot of representative sample statistics is called a(n) :

A) Gantt chart.
B) simo chart.
C) control chart.
D) up-down matrix.
E) standard deviation table.

F) A) and D)
G) B) and E)

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Question 23

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An analyst counted 17 A/B runs and 15 U/D runs in 26 time series observations. Do these results suggest that the data are non-random?

Which of the following quality control sample statistics indicates a quality characteristic that is an attribute?

Perform run tests on the given data. What can you conclude? $\begin{array} { l c } \text { Sample } & \text { Defectives } \\\hline 1 & 18 \\2 & 24 \\3 & 19 \\4 & 22 \\5 & 20 \\6 & 19 \\7 & 22 \\8 & 23 \\9 & 25 \\10 & 17 \\11 & 20 \\12 & 23 \\13 & 21 \\14 & 16\end{array}$

A stent for use in coronary surgery requires a special coating. Specifications for this coating call for it to be at least 0.05 millimeters but no more than 0.15 millimeters. Suppose the long-run average of this coating process is 0.09 millimeters. Further suppose this process's standard deviation is 0.015 millimeters. What proportion of the output from this process will fail to meet specifications?

The purpose of statistical process control is to ensure that historical output is random.

The chair of the operations management department at Quality University wants to construct a p-chart for determining whether the four faculty teaching the basic P/OM course are under control with regard to the number of students who fail the course. Accordingly, he sampled 100 final grades from last year for each instructor, with the following results: $\begin{array} { l c } \text { Instructor } & \text { Number of Failures } \\\hline \text { Prof. A } & 13 \\\text { Prof. B } & 0 \\\text { Prof. C } & 11 \\\text { Prof. D } & 16\end{array}$ What is the sample proportion of failures (p) for Prof. D?

If a point on a control chart falls outside one of the control limits, this suggests that the process output is nonrandom and should be investigated.

The amount of inspection we choose can range from no inspection at all to inspecting each item numerous times.

Approximately 99.7 percent of sample means will fall within plus or minus two standard deviations of the process mean if the process is under control.

A stent for use in coronary surgery requires a special coating. Specifications for this coating call for it to be at least 0.05 millimeters but no more than 0.15 millimeters. Assuming that the process mean of 0.09 cannot be changed, what process standard deviation would be required for this process to be considered capable (assuming that a capable process must have a capability index of at least 1.3)?

Quality control, in contrast to quality assurance, is implemented:

A process results in a few defects occurring in each unit of output. Long-run, these defects should be monitored with:

Concluding that a process is out of control when it is not is known as a Type I error.

A lower control limit must by definition be a value less than an upper control limit.

The process capability index (indicated by C_pk) can be used only when the process is centered.

Statistical process control is the measurement of rejects in the final product.

The variation of a sampling distribution is tighter than the variation of the underlying process distribution.

Given the following process control data for a quality attribute (three samples of size 400 each): $\begin{array} { l r } \text { Sample } & \text { Defectives } \\\hline \# 1 & 36 \\\# 2 & 32 \\\# 3 & 52\end{array}$ If the process is known to produce 11 percent defectives on average, what is the alpha risk (probability of Type I error) for upper and lower control limits of .1256 and .0944 respectively? .1412 and .0788? .1568 and .0632?